AngioGraphCAD models coronary arteries as graphs, letting a graph neural network assess lesion-level risk the way cardiologists reason — one lesion at a time.
A team from Imperial College London, Royal Brompton Hospital, and TU Munich built a framework that combines variable CAIPIRINHA acquisition with artefact-aware dual-branch deep learning to achieve 18-fold acceleration in cardiac diffusion tensor imaging while cutting key biomarker errors by…
Researchers at Southwest University built a two-stage federated learning framework that measures how similar different hospitals’ model updates are — layer by layer — then uses that similarity to allocate smarter aggregation weights and automatically pick which layers to keep…
FedLSC: Federated Learning with Layer Similarity Comparison for Skin Cancer Read More »
Researchers from KTO Karatay University and Selcuk University flipped the standard deep learning script — instead of augmenting their way out of class imbalance, they rewired the reward system of a Deep Q-Network so that correctly identifying a rare Dermatofibroma…
Class-Weighted DQN for Skin Cancer Classification Read More »
The early detection and accurate grading of cancer remains one of modern medicine’s most pressing challenges. For pathologists worldwide, the assessment of gland morphology in histopathological images serves as the gold standard for cancer diagnosis—particularly in colorectal and prostate cancers.…
DPFR: A Breakthrough in AI-Powered Gland Segmentation for Cancer Diagnosis Read More »
Cancer remains one of the leading causes of mortality worldwide, yet advances in personalized medicine and artificial intelligence are fundamentally transforming how physicians predict patient survival and recommend treatment strategies. Traditional prognostic approaches rely on limited clinical variables and single-source…
In the high-stakes world of neuro-oncology, time is not just a factor—it’s a lifeline. The journey from an initial MRI scan to a definitive brain tumor diagnosis has long been fraught with delays, human error, and the immense cognitive load…
Picture a radiology department that wants an AI tool to outline kidneys on ultrasound scans. The best open segmentation model weighs hundreds of megabytes and was trained on everyday photos of cats, cars and coffee mugs. The department has eighty…
Task-Specific Knowledge Distillation for Medical Image Segmentation Read More »
Cardiac Magnetic Resonance (CMR) imaging has become an indispensable tool in modern cardiology, providing clinicians with detailed anatomical and functional information about the heart. However, a significant limitation persists in clinical practice: the acquisition of only sparse 2D short-axis slices…
Cardiovascular diseases remain the leading cause of death worldwide, with coronary artery disease (CAD) at the forefront. Early and accurate detection of coronary stenosis—narrowing of the arteries supplying the heart—is critical for timely intervention and improved patient outcomes. While invasive…